Experimental Evaluations on 4-By-2 MU-MIMO Achieving 1 Gbps Throughput Using AMC with Outer-Loop Threshold Control for LTE-Advanced Downlink

This paper presents laboratory experimental results on 4-by-2 multi-user (MU)-MIMO multiplexing with two mobile stations (MSs) in the LTE-Advanced downlink in combination with carrier aggregation (CA) using 5 component carriers (CCs). Extended channel state information (CSI) feedback functionality based on eigenvalue decomposition (EVD) is implemented into real-time experimental equipment based on the LTE-Advanced radio interface to support MU-MIMO operations applying minimum mean square error (MMSE)-based precoding. Laboratory experiments are conducted assuming a multi-path fading environment based on different antenna configurations. The experimental results show that 4-by-2 MU-MIMO with two data streams per MS achieves a peak throughput of greater than 950 Mbps, i.e., nearly 1 Gbps, in a correlated antenna configuration scenario when the maximum Doppler frequency is 10 Hz and the propagation channel model with the root mean squared delay spread is 0.3 μsec. The results also show that, high throughput performance such as greater than 750 Mbps for 4-by-2 MU-MIMO with two data streams per MS is achieved even in a non-correlated antenna configuration scenario although the environment is limited to low mobility and a small delay spread.

This paper proposes a highly accurate signal to noise ratio (SNR) estimation method for adaptive modulation and coding (AMC) by learning power spectral density (PSD) images with a convolutional neural network (CNN). Accurate SNR estimation is indispensable for adaptive control schemes such as AMC. Proposed method trains the CNN using PSD images and the corresponding SNR value as a teacher signal, and outputs the SNR in response to an input of unknown PSD image. Once trained, the SNR can be estimated with high speed and high accuracy, so AMC performance can be improved. Furthermore, since PSD is hardly affected by the Doppler shift, proposed method is resistant to high-speed environment. Compared with the previously proposed method which estimates SNR from a PSD data using a neural network, the proposed method can improve the estimation accuracy, bit error rate (BER) and throughput performance when AMC is applied.

This paper presents the performance of outer-loop control for adaptive modulation and coding (AMC) using mutual information (MI) based mapping between the block error rate (BLER) and received signal-to-interference plus noise power ratio (SINR) in the multiple-input multiple-output (MIMO)-orthogonal frequency division multiplexing (OFDM) downlink employing maximum likelihood detection (MLD). In AMC, we generate a mapping table between the BLER and MI per bit in advance, which is computed from the received SINR, assuming typical channel conditions including the path model and fading maximum Doppler frequency. Then, in the proposed outer-loop control, the measured MI per bit value for selecting the best modulation and coding scheme (MCS) is adjusted so that the measured BLER after turbo decoding satisfies the prescribed target value. Computer simulation results show that the outer-loop control achieves almost the same throughput as that with a mapping table assuming channel conditions identical to those for the actual measurement, while achieving nearly the identical target BLER. Moreover, we show that the best step size, which provides nearly the maximum throughput, differs according to the change in the maximum Doppler frequency in contrast to the relative feedback delay of the AMC loop. Nevertheless, it is insensitive to the target BLER value and frequency-selectivity of a channel model.

In this paper, we combine adaptive modulation and coding (AMC) with multiple input multiple output (MIMO) VBLAST multiplexing to improve the throughput performance of AMC in next generation mobile communication systems. In addition, we propose a system that adopts selection transmit diversity (STD) in the combined AMC-MIMO VBLAST system. The received signal-to-noise ratio (SNR) is improved by adopting STD techniques and an improved SNR increases a probability of selecting modulation and coding scheme (MCS) level that supports higher data rate. From the simulation results, the investigated MIMO-STD VBLAST system provides a throughput gain of 1Mbps compared with simply combined AMC-MIMO VBLAST system when the required SNR is 15dB. Also, the higher throughput is achieved by AMC-TD schemes and AMC-STTD scheme provides about 250kbps increase in throughput. And AMC-STD with 2 transmit antennas achieves about 420 kbps throughput improvement over the conventional AMC at 9dB SNR.

A new and effective algorithm is proposed in this paper based on Gaussian Mixture Modeling (GMM) and Minimum Mean Square Error (MMSE) criterion for speech enhancement. GMM mean vectors are used to model the space span by the power spectra of the input noisy speech frames. No assumption is made on the nature or stationarity of the noise. No Voice Activity Detection (VAD) or any other means is used to estimate the input Signal to Noise Ratio (SNR). The mean vectors derived from mixture models of Power Spectral Densities (PSDs) of speech and different noise sources are used to form sets of over-determined system of equations, as many as noise source candidates, whose solutions lead to the MMSE estimations of speech and noise power spectra. These are then used for noise suppression by applying Wiener filtering carried out on overlapping frames. The input SNR is estimated and the nature of the noise involved is determined as by-products of the method used. Results are compared with those of two variants of a method based on approximate but explicit MMSE Bayesian estimation that show good results but suffer from long processing times. It is shown that, at the cost of a slight lower improvement in SNR and PESQ score, the new algorithm reduces the computation time to 1/30 which makes it suitable for practical applications.

Orthogonal frequency division multiplexing (OFDM) with adaptive coding and modulation (ACM) gives a communication system that can adapt to varying channel conditions and provide reliable communication at a wider range of signal to noise-ratios (SNRs). We investigate how the number of available transmission rates in the ACM scheme impacts communication performance and feedback requirements. To accommodate for the various rates in the ACM system we use serial concatenated trellis-coded modulation (SCTCM) consisting of a rate-compatible punctured convolutional (RCPC) code or a woven serial concatenated convolutional (WSCC) code, both with a rate-1 inner accumulate code and mapping to a Gray-labeled signal constellation. We show that significant reductions in complexity and corresponding savings in protocol overhead can be obtained without significant performance degradation. It is shown that an equal spacing of available rates over the expected range of SNRs is preferable to an uneven spacing.

In downlink multiple streams multiple-input multiple-output (MIMO) system, adaptive modulation and coding (AMC) is used to increase spectrum efficiency (SE) due to selecting the modulation and coding rate scheme (MCS) dynamically. However, there is a gap between UE's signal to interference plus noise ratio (SINR) and that required by the MCS. In this paper, we propose a novel power loading algorithm using the SINR gap. The algorithm converts the SINR gap into the transmit power gap among different streams. Thus BS adjusts transmit power allocation for different streams and selects higher MCS than that without adjusting power. The results demonstrate that this proposed algorithm contributes large gain of SE for single user (SU-) MIMO based on singular value decomposition (SVD) preceding.

In this paper, we propose a throughput optimization scheme for relay protocols based on Adaptive Modulation and Coding (AMC). The performance of relay protocols with the AMC scheme and show that relay protocols with the AMC scheme are capable of providing better average throughput at a lower Signal to Noise Ratio (SNR) level as compared to the conventional scheme with no AMC. We perform 3GPP Long Term Evolution-Advanced (LTE-A) parameters based simulations to prove the performance comparison of adaptive Modulation and Coding Scheme (MCS) relay protocols with non-adaptive MCS relay protocols. The simulation results of the proposed system with adaptive MCS prove that among the Amplify-and-Forward (AF), Decode-and-Forward (DF) and De-Modulate-and-Forward (DMF), the DMF protocol performs best, at a lower SNR value and higher average throughput.

The paper proposes a new set of normalization techniques for precoding/beamforming matrices applicable to broadband multiuser multiple-input multiple-output (MIMO) satellite systems. The proposed techniques adapt known normalization methods to account for the signal attenuation experienced by users due to the degradation of antenna gain and free space losses towards the edge of the coverage. We use, as an example, an array-fed reflector (AFR) antenna onboard a satellite in geosynchronous orbit (GEO), which provides a favorable trade-off between high-directivity, reconfigurability, and the requirement for digital processing, but suffers from high scan losses away from broadside due to optical aberrations when considered for global coverage applications. Three different precoding/beamforming techniques are employed, namely zero forcing (ZF), minimum mean squared error (MMSE), and matched filtering (MF). Low-complexity power normalization techniques digitally applied after the beamformer are introduced that, in the absence of any atmospheric effects, lead to iso-flux-like characteristics whilst satisfying the power constraint per feed. In comparison with other methods reported in the literature, mainly based on iterative algorithms, the proposed techniques consist in closed-form expressions to provide uniform signal-to-noise ratio (SNR) and signal-to-noise plus interference ratio (SNIR) across the users without significant impact on the payload sum rate. Numerical results are presented to comparatively demonstrate the achieved performance in terms of total capacity and distribution of SNR and SNIR at various noise and interference scenarios.

This work focuses on studying signal detection using three different equalization techniques, namely: Zero Forcing (ZF), Minimum Mean Square Error (MMSE) and Beam Forming (BF), for a 4×4 MIMO-system. Results show that ZF equalization is the simplest technique for signal detection, However, Beam Forming (BF) gives better Bit Error Rate (BER) performances at high Signal to Noise Ratio (SNR) values with some complexity in design. For more antennas at the base station, it is too complex to design the weight matrix for ZF, however, it is suitable for BF with the help of good quality digital signal processors. Performance of MIMO-system, with 8 antennas at the base station using BF equalization, is analysed to get BER values at different SNR. Results show a considerable improvement in BER for 8 antennas at the base station.

Adaptive modulation and coding (AMC) technique can be applied in underwater acoustic communications to improve the system data rate as well as the robustness in varying channel conditions. In this paper, we demonstrate an OFDM based AMC operation using a number of transmission modes with different data rates. We propose to use the effective signal-to-noise ratio (SNR) computed after channel estimation and channel decoding as performance indicator for mode switching, instead of input SNR and pilot SNR. Real time AMC tests have been conducted in a recent sea experiment.

This paper presents a performance model of a wireless network with one-antenna transmitter scheduling information towards a set of terminals in a time-division fashion. Each terminal is enabled with a multiple-antenna maximum ratio combining (MRC) receiver. The objective of this model is to evaluate the performance of adaptive modulation and coding (AMC) in Rayleigh fading channels under two assumptions: 1) correlation between antennas, and 2) user scheduling based on maximum channel gain. The model is useful for cross-layer design purposes, as it provides a relatively low-complex representation of the physical-layer. Closed-form expressions are here derived of correct packet reception probabilities for different modulation and coding schemes (MCSs) with different values of block error rate (BLER) and spectral efficiency. Analytic expressions are derived with the help of the theory of order statistics, which allows for the study of the statistics of channel-aware scheduling. The results indicate that correlation does not always reduce performance. At low signal-to-noise ratio (SNR), correlation can improve performance rather than reducing it. By contrast, at high SNR, correlation is shown to always reduce the performance of the receiver. This low-SNR behavior is less evident as the number of antennas increases and more evident when the number of users included in the scheduling process increases.

In this paper, linear precoding (LP) algorithm has been studied to improve the bit error rate (BER) performance of large scale multiple input multiple output (MIMO) system. A new technique of enhancing the BER performance of linear precoding algorithm without complexity in hardware and mathematical calculations is proposed and it is used on a traditional LP algorithms like a Maximum Ratio Transmission (MRT), a Zero-Forcing (ZF), a Regularized Zero-Forcing (RZF), and a Minimum Mean Square Error (MMSE) for Millimeter wave MU-MIMO communication system. A new technique is also used to mitigate the BER gab problem between (ZF, MMSE) and (RZF, MMSE) linear precoding algorithms. The result shows that with using the new technique, the BER performance of modified LP significantly outperform their traditional LP by 10−5 when using 4 element of BS antenna, 10−6 when using 16 element of BS antenna and mitigate the BER gab problem at different signal to noise ratio (SNR).

Free space optical communication (FSO) is widely deployed to transmit high data rates for rapid communication traffic increase. Asymmetrically clipped optical orthogonal frequency division multiplexing (ACO-OFDM) modulation is a very efficient FSO communication technique in terms of transmitted optical power. However, its performance is limited by atmospheric turbulence. When the channel includes strong turbulence or is non-deterministic, the bit error rate (BER) increases. To reach optimal performance, the ACO-OFDM decoder needs to know accurate channel state information (CSI). We propose novel detection using different deep learning (DL) algorithms. Our DL models are compared with minimum mean square error (MMSE) detection methods in different turbulent channels and improve performance especially for non-stationary and non-deterministic channels. Our models yield performance very close to that of the MMSE estimator when the channel is characterized by weak or strong turbulence and is stationary. However, when the channel is non-stationary and variable, our DL model succeeds in improving the performance of the system and decreasing the signal to noise ratio (SNR) by more than 8 dB compared to that of the MMSE estimator, and it succeeds in recovering the received data without needing to know accurate CSI. Our DL decoders also show notable speed and energy efficiency improvement.

In this paper, we propose a cross-layer design which combines adaptive modulation and coding (AMC) at the physical layer with a hybrid automatic repeat request (HARQ) protocol at the data link layer to minimize the packet error rate (PER) and maximize the spectral efficiency. By using Markov model to predict the channel condition of next frame according to the second order statistics characteristics of the former frame, we calculate the conditional probability density function and joint probability density function of signal to noise ratio (SNR). Further, we derive the packet error rate and average spectral efficiency in closed-form for transmission over Nakagami-m fading channels. Numerical results show that the proposed scheme can obtain lower PER and higher spectral efficiency c ompared with traditional HARQ protocol s. The cross-layer design scheme combing type-III HARQ with AMC can achieve the highest spectral efficiency and the lowest PER than type-I HARQ and type-II HARQ.